Systems and methods for pallet identification

ABSTRACT

Provided are methods, including computer-implemented methods, devices, and computer-program products applying systems and methods for pallet identification. According to some embodiments of the invention, a pallet may be visually identified through photographs without attaching physical labels. Thus, the status of pallets may be monitored (e.g., their location and structural integrity) as they move through the supply chain.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/969,195, filed May 2, 2018, which is incorporated herein byreference. U.S. patent application Ser. No. 15/969,195 claims thebenefit of U.S. Provisional Patent Application No. 62/500,462, filed May2, 2017, which is incorporated herein by reference.

FIELD

The present disclosure generally relates to cargo transportationutilizing pallets, and more specifically to systems and methods forpallet identification using visual features.

BACKGROUND

Monitoring pallet movement through a supply and distribution chain canaid in diagnosing issues with pallet loss and recovery, pallet damageand pallet cycle time. To achieve comprehensive monitoring, each palletmust be labeled with a unique identifier. In conventional systems, theunique identifier is indicated and/or stored on a physical device, suchas a numerical tag, a bar code, an RFID tag, or an electronic device.However, physically attached identification devices can easily becomedamaged or fall off when the pallet is moved through the supply chain.

BRIEF SUMMARY

Provided are methods, including computer-implemented methods, devices,and computer-program products applying systems and methods for palletidentification. According to some embodiments of the invention, a palletmay be visually identified through photographs with or without attachingphysical labels, such as bar codes, QR codes, serial numbers, stencils,brands, embossing, stamps, etc. Thus, the status of pallets may bemonitored (e.g., their location and structural integrity) as they movethrough the supply chain.

According to some embodiments of the invention, a computer-implementedmethod is provided. The method comprises receiving, at a server computerlocated in a cloud, an image file depicting a plurality of visualfeatures organized in a plurality of spatial orientations on a pallet.The image file was generated by an imaging device located at a facilityhousing the pallet in a supply chain. The pallet is included in aplurality of known pallets in the supply chain. The method furthercomprises generating a set of unidentified vectors associated with thepallet using the plurality of visual features and the plurality ofspatial orientations. The method further comprises accessing a databasestoring a plurality of sets of known vectors in association with aplurality of known pallet identifiers corresponding to the plurality ofknown pallets in the supply chain. The method further comprisescomparing the set of unidentified vectors to the plurality of sets ofknown vectors to identify a matching set of known vectors and anassociated known pallet identifier. The method further comprisesgenerating data associated with the pallet. The method further comprisesstoring the data as an entry in the database corresponding to theassociated known pallet identifier.

According to some embodiments of the invention, a device is provided.The device comprises one or more processors. The device furthercomprises a non-transitory computer-readable medium containinginstructions that, when executed by the one or more processors, causethe one or more processors to perform operations including the steps ofthe methods described herein.

According to some embodiments of the invention, a computer-programproduct is provided. The computer-program product is tangibly embodiedin a non-transitory machine-readable storage medium of a device. Thecomputer-program product includes instructions that, when executed byone or more processors, cause the one or more processors to performoperations including the steps of the methods described herein.

This summary is not intended to identify key or essential features ofthe claimed subject matter, nor is it intended to be used in isolationto determine the scope of the claimed subject matter. The subject mattershould be understood by reference to appropriate portions of the entirespecification of this patent, any or all drawings, and each claim.

The foregoing, together with other features and embodiments, will becomemore apparent upon referring to the following specification, claims, andaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrative embodiments of the present invention are described indetail below with reference to the following drawing figures:

FIG. 1 is a bottom perspective view of a pallet with a beacon, inaccordance with some embodiments.

FIG. 2 is a side view of a pallet with a load, in accordance with someembodiments.

FIG. 3 is a block diagram illustrating a pallet, in accordance with someembodiments.

FIG. 4 is a block diagram illustrating a system for palletidentification, in accordance with some embodiments.

FIG. 5 is a block diagram illustrating an access device, in accordancewith some embodiments.

FIG. 6 is a block diagram illustrating a server computer, in accordancewith some embodiments.

FIG. 7 is a flow chart illustrating a method for pallet identification,in accordance with some embodiments.

DETAILED DESCRIPTION

Certain aspects and embodiments of this disclosure are provided below.Some of these aspects and embodiments may be applied independently andsome of them may be applied in combination as would be apparent to thoseof skill in the art. In the following description, for the purposes ofexplanation, specific details are set forth in order to provide athorough understanding of embodiments of the invention. However, it willbe apparent that various embodiments may be practiced without thesespecific details. The figures and description are not intended to berestrictive.

The ensuing description provides exemplary embodiments only, and is notintended to limit the scope, applicability, or configuration of thedisclosure. Rather, the ensuing description of the exemplary embodimentswill provide those skilled in the art with an enabling description forimplementing an exemplary embodiment. It should be understood thatvarious changes may be made in the function and arrangement of elementswithout departing from the spirit and scope of the invention as setforth in the appended claims.

Specific details are given in the following description to provide athorough understanding of the embodiments. However, it will beunderstood by one of ordinary skill in the art that the embodiments maybe practiced without these specific details. For example, circuits,systems, networks, processes, and other components may be shown ascomponents in block diagram form in order not to obscure the embodimentsin unnecessary detail. In other instances, well-known circuits,processes, algorithms, structures, and techniques may be shown withoutunnecessary detail in order to avoid obscuring the embodiments.

Also, it is noted that individual embodiments may be described as aprocess which is depicted as a flowchart, a flow diagram, a data flowdiagram, a structure diagram, or a block diagram. Although a flowchartmay describe the operations as a sequential process, many of theoperations can be performed in parallel or concurrently. In addition,the order of the operations may be re-arranged. A process is terminatedwhen its operations are completed, but could have additional steps notincluded in a figure. A process may correspond to a method, a function,a procedure, a subroutine, a subprogram, etc. When a process correspondsto a function, its termination can correspond to a return of thefunction to the calling function or the main function.

The term “computer-readable medium” includes, but is not limited to,portable or non-portable storage devices, optical storage devices, andvarious other mediums capable of storing, containing, or carryinginstruction(s) and/or data. A computer-readable medium may include anon-transitory medium in which data can be stored and that does notinclude carrier waves and/or transitory electronic signals propagatingwirelessly or over wired connections. Examples of a non-transitorymedium may include, but are not limited to, a magnetic disk or tape,optical storage media such as compact disk (CD) or digital versatiledisk (DVD), flash memory, memory or memory devices. A computer-readablemedium may have stored thereon code and/or machine-executableinstructions that may represent a procedure, a function, a subprogram, aprogram, a routine, a subroutine, a module, a software package, a class,or any combination of instructions, data structures, or programstatements. A code segment may be coupled to another code segment or ahardware circuit by passing and/or receiving information, data,arguments, parameters, or memory contents. Information, arguments,parameters, data, etc. may be passed, forwarded, or transmitted via anysuitable means including memory sharing, message passing, token passing,network transmission, or the like.

Furthermore, embodiments may be implemented by hardware, software,firmware, middleware, microcode, hardware description languages, or anycombination thereof. When implemented in software, firmware, middlewareor microcode, the program code or code segments to perform the necessarytasks (e.g., a computer-program product) may be stored in acomputer-readable or machine-readable medium. A processor(s) may performthe necessary tasks.

Pallets

A pallet may be a structure that supports physical assets for storage,presentation, handling, and/or transportation. As used herein, the term“pallet” may be used to describe any load carrier, including any type ofplatform, dolly, bin, container, and the like. The physical assets maybe any physical assets, such as perishable or nonperishable physicalgoods. FIG. 1 is a bottom perspective view of a pallet 100, inaccordance with some embodiments. The pallet 100 may include a base 120and legs 110. The pallet 100 may be of any size, shape, and/ordimension, and may be made of any material or combination of materials.The base 120 and legs 110 may be of any size, shape, and/or dimensions.The base 120 may be flat and/or otherwise configured to support theshape and/or weight of the physical asset to be held on the pallet 100.Although shown as having a particular design in FIG. 1, it iscontemplated that any design may be incorporated on or in the base 120.For example, the base 120 may have smaller, larger, fewer, more,differently shaped, or differently placed spacing than those shown inFIG. 1, depending on characteristics of the particular physical asset tobe placed on the base 120 (e.g., weight, shape, temperaturerequirements, size, etc.).

The legs 110 may be sized and positioned to support the particularphysical asset. In some embodiments, the legs 110 may be sized andpositioned to allow a forklift, crane, or jacking device to engage andlift the pallet 100 between the legs 110. Although shown and describedas having three legs 110, it is contemplated that the pallet 100 mayhave any suitable number of legs or no legs. For example, in someembodiments, the pallet 100 may include a base 120 on both the top andbottom of the pallet 100 with no legs. In another example, for heavierphysical assets, the pallet 100 may include one or more additional legscentrally located with respect to the pallet 100 to prevent sagging ofthe base 120. Further, although shown and described as being in aparticular orientation and having a particular size, it is contemplatedthat the legs 110 may be of any size (e.g., height, length, width,depth, etc.) and/or orientation (e.g., parallel to each other,perpendicular to each other, etc.).

The pallet 100 may be made of any suitable material, depending on thecharacteristics of the particular physical asset to be supported by thepallet 100. For example, the pallet 100 may be wooden, plastic, and/ormetal. In some embodiments, the pallet 100 may be constructed to includeunique physical features. In some embodiments, the base 120 may be madeof a same or different material than the legs 110. In some embodiments,the base 120 and the legs 110 may form a single unitary body (e.g.,formed from a single mold). In some embodiments, the base 120 may beremovable from one or more of the legs 110.

In some embodiments, additional components may be integrated with thepallet 100. For example, the underside of the pallet 100 may include abeacon 150. The beacon 150 may include a number of differentfunctionalities. For example, the beacon 150 may be programmed with thetype of physical asset located on the pallet 100 and/or an identifier ofthe pallet 100. The beacon 150 may further include or be in operablecommunication with one or more sensors configured to monitor certainconditions of the pallet 100 (e.g., environmental conditions, movements,etc.). The beacon 150 is described further herein with respect to FIG.3. Although shown as being located in a particular position on thepallet 100, it is contemplated that the beacon 150 may be located in anysuitable position on the pallet 100. FIG. 2 is a side view of anotherexemplary pallet 200 with a load 220 placed atop the pallet 200 fortransportation, storage, presentation, etc. As used herein, pallet 100may be referred to interchangeably with pallet 200.

The pallet 100 and/or 200 may include components for performing multiplefunctions, as described herein. FIG. 3 is a block diagram illustratingthe system components of the pallet 100 and/or 200, in accordance withsome embodiments. The pallet 100 and/or 200 may include a beacon 115 inoperative communication with one or more external sensors 350. Thebeacon 115 may include device hardware coupled to a memory 340. Thedevice hardware may include a processor 325, a communication subsystem330, internal sensors 335, and a power supply 345. In some embodiments,the beacon 115 may be implemented as an active tag (e.g., an RFID tag).The beacon 115 may be associated with an identifier (e.g., an active tagidentifier).

The processor 325 may be implemented as one or more integrated circuits(e.g., one or more single core or multicore microprocessors and/ormicrocontrollers), and may be used to control the operation of thebeacon 115. The processor 325 can execute a variety of programs inresponse to program code or computer-readable code stored in memory 340,and can maintain multiple concurrently executing programs or processes.The communication subsystem 330 may include one or more transceiversand/or connectors that can be used by the beacon 115 to communicate withother devices (e.g., the external sensors 350, access devices, etc.)and/or to connect with external networks. In some embodiments, thecommunication subsystem 330 may be configured to communicate using morethan one protocol (e.g., protocol A 332 and protocol B 333). Protocol A332 and protocol B 333 may be two different wired or wirelesscommunication protocols. For example, protocol A 332 and protocol B 333may be selected from the group including Bluetooth, Bluetooth LE, nearfield communication, WiFi, cellular communication, Ethernet, fiberoptics, etc. The particular protocol used for a particular communicationmay be determined based on any of a number of factors, includingavailability, signal strength, type and/or amount of power received fromor remaining on power supply 345, data throughput, type of data to becommunicated, size of data to be communicated, and the like.

The internal sensors 335 may include any movement-related,location-related, and/or environmental-related sensors. For example, theinternal sensors 335 may include a global positioning system (GPS), anaccelerometer, a gyroscope, a barometer, a thermometer, a humiditysensor, a light sensor, a microphone, combinations thereof, and/or thelike. The internal sensors 335 may be coupled to the communicationsubsystem 330, such that sensor measurements may be transmitted off ofthe pallet 100 to other devices or systems, as described further herein.

The memory 340 may be implemented using any combination of any number ofnon-volatile memories (e.g., flash memory) and volatile memories (e.g.,DRAM, SRAM), or any other non-transitory storage medium, or acombination thereof media. In some embodiments, the memory 340 may beincluded in the processor 325. The power supply 345 may include anywired or wireless power supply, such as a power outlet supply, a solarpanel, and/or a battery.

The beacon 115 may be coupled to one or more external sensors 350 on thepallet 100. The external sensors 350 may include, for example, a weightsensor and/or any of the sensors described above with respect to theinternal sensors 335. In one example, the weight sensor may includecircuitry that measures the weight of a load on the pallet 100. Theweight sensor may transmit the weight to the beacon 115. The beacon mayuse the communication subsystem 330 to transmit this data off of thepallet 100 to other devices or systems, as described further herein.

Systems for Pallet Identification

In some cases, it may be desirable to identify a pallet. According tosome embodiments of the invention, a pallet may be visually identifiedthrough photographs without attaching physical tags or labels. Thus, thestatus of pallets may be monitored (e.g., their location and/orstructural integrity) as they move through the supply chain. Further,physical devices may not be necessary to identify the pallets, which maybe desirable as they may become damaged, come loose, become destroyed,or get separated from the pallets as they move through the supply chain.

FIG. 4 is a block diagram illustrating a system for palletidentification, in accordance with some embodiments. The system mayinclude a pallet 100, an access device 410, a server computer 420, adatabase 425, and a controller computer 430. The pallet 100 and theaccess device 410 may be located at a facility 405 in the supply chain,such as a warehouse or store. The server computer 420 and the database425 may be located in the cloud, such as at one or more offsite or thirdparty locations with online or networked storage. The controllercomputer 430 may be located at a controller location, such as at apallet logistics and tracking company. Although shown and described withrespect to a certain number of entities performing certain functions, itis contemplated that a greater or fewer number of entities may performthe functions described herein. For example, the functions of the servercomputer 420 may be spread across multiple server computers. In anotherexample, the database 425 may be incorporated internally to the servercomputer 420. In still another example, the functions of the servercomputer 420 may be partially or wholly be performed by the accessdevice 410.

In some embodiments, the pallet 100 may communicate data to the accessdevice 410 to cause the access device 410 to perform one or moreoperations. For example, the pallet 100 may communicate (or cause to becommunicated) a signal indicating that the pallet 100 is within a visualrange of the access device 410. The signal may be communicated, forexample, by a Bluetooth or Bluetooth LE tag on the pallet 100. When theaccess device 410 receives the signal, the access device 410 may capturean image of the pallet 100 using a camera or other image capturehardware and/or software, as described further herein. For example, theaccess device 410 and/or the pallet 100 may implement a photoeye orphotoelectric sensor. In some embodiments, the pallet 100 may notinclude a tag capable of short range communication. Thus, the accessdevice 410 may be manually caused to capture an image of the pallet 100in some embodiments (e.g., by selecting an image capture option on theuser interface). This may happen at any time or interval, such as whenthe pallet 100 enters the facility 405, when the pallet 100 is leavingthe facility 405, once a day, etc.

The access device 410 may be any suitable electronic user device. Theaccess device 410 may include a communication device. A communicationdevice may provide remote communication capabilities to a network.Examples of remote communication capabilities include using a mobilephone (wireless) network, wireless data network (e.g., 3G, 4G or similarnetworks), Wi-Fi, Wi-Max, or any other communication medium that mayprovide access to a network such as the Internet or a private network.Examples of devices include mobile phones (e.g., cellular phones), PDAs,tablet computers, net books, laptop computers, personal music players,handheld specialized readers, watches, fitness bands, wearables, anklebracelets, rings, earrings, key fobs, physical wallets, glasses,containers, coffee mugs, takeout containers, etc., as well asautomobiles with remote communication capabilities. The access device410 may comprise any suitable hardware and software for performing suchfunctions, and may also include multiple devices or components (e.g.,when a device has remote access to a network by tethering to anotherdevice—i.e., using the other device as a modem—both devices takentogether may be considered a single communication device). Furtherexamples of an access device 410 may include a POS or point of saledevice (e.g., POS terminals), cellular phone, PDA, personal computer(PCs), tablet PC, hand-held specialized reader, set-top box, electroniccash register (ECR), virtual cash registers (VCR), kiosk, and the like.

The access device 410 may have an application installed that allows itto upload the image file depicting the pallet 100 to a server computer420. The image file of the pallet 100 may include visual featuresorganized in spatial orientations. For example, the visual features mayinclude a unique or uncommon set of markings on the pallet 100, such asletters, numbers, symbols, graphics, colors, marks, dents, scratches,patterns, grains, etc. In embodiments in which the pallet 100 is wooden,the visual features may include wood grain marks and patterns, such as adirection of the wood cells (e.g., straight grain, spiral grain,interlocked, etc.), surface appearance, growth ring placement, plane ofthe cut (quarter sawn, flat sawn, end grain, etc.), rate of growth,relative cell size, etc. The spatial orientations may describe thedistance between visual features and/or the orientation of visualfeatures with respect to each other.

The access device 410 may be in communication with the server computer420. The access device 410 may forward the image file of the pallet 100to the server computer 420. The server computer 420 may generate a setof unidentified vectors associated with the pallet 100 using the visualfeatures and the spatial orientations. The server computer 420 mayaccess a database 425 storing sets of known vectors in association withknown pallet identifiers corresponding to known pallets in the supplychain. For example, each pallet in the supply chain may be assigned apallet identifier that uniquely identifies the pallet, and may be storedin association with vectors generated based on the visual features andspatial orientations of each pallet. The server computer 420 may comparethe set of unidentified vectors corresponding to the pallet 100 to thesets of known vectors to identify a matching set of known vectors andits associated known pallet identifier from the database 425. In someembodiments, the server computer 420 may identify a lack of a pallet inan image. In some embodiments, the server computer 420 may identifymultiple pallets in an image, and may process one pallet image at atime.

The server computer 420 may generate data associated with the pallet 100once it is identified, and store the data as an entry in the database425 corresponding to the associated known pallet identifier. Forexample, the server computer 420 may generate data noting differencesbetween the image file of the pallet 100 just collected and the storedset of vectors associated with the pallet 100. Such data may beindicative of damage to the pallet 100. In another example, the servercomputer 420 may generate location data for the pallet 100 (e.g., dataindicative of the facility 405). In some embodiments, the servercomputer 420 may provide this data from the database 425 to a controllercomputer 430. The controller computer 430 may be an entity that tracks,maintains, and/or owns the pallet 100. The controller computer 430 mayuse this data to invoice shippers, carriers, and/or customers for damageto the pallet 100, to determine whether the pallet 100 is at the correctfacility 405, to determine where the pallet 100 is in the supply chain,to determine the cycle time of the pallet 100, to predict timing of thepallet 100 at a particular location, etc.

In some embodiments, the functions of the server computer 420 may beperformed wholly or partially by the access device 410. For example, insome embodiments, the size of the transmission sent to the servercomputer 420 by the access device 410 may be reduced by performing theimage analysis and feature extraction on the access device 410. Theunidentified vectors may further be generated by the access device 410based on the image analysis and feature extraction. The data vectors,which have a small memory footprint, may then be transmitted to theserver computer 420 and run through the database 425.

FIG. 5 is a block diagram illustrating an access device 410, inaccordance with some embodiments. The access device 410 may includedevice hardware 504 coupled to a memory 502. Device hardware 504 mayinclude a processor 505, a camera 508, a communication subsystem 509,and a user interface 506. In some embodiments, device hardware 504 mayinclude a display 507 (which can be part of the user interface 506).

Processor 505 can be implemented as one or more integrated circuits(e.g., one or more single core or multicore microprocessors and/ormicrocontrollers), and is used to control the operation of the accessdevice 410. Processor 505 can execute a variety of programs in responseto program code or computer-readable code stored in memory 502, and canmaintain multiple concurrently executing programs or processes.Communication subsystem 509 may include one or more transceivers and/orconnectors that can be used by access device 410 to communicate withother devices (e.g., the pallet 100) and/or to connect with externalnetworks (e.g., to connect to the server computer 420). User interface506 can include any combination of input and output elements to allow auser to interact with and invoke the functionalities of the accessdevice 410. In some embodiments, user interface 506 may include acomponent such as display 507 that can be used for both input and outputfunctions. Camera 508 may be implemented as hardware in conjunction withsoftware to capture visual features and/or images of pallets, forexample, as described further herein. Memory 502 can be implementedusing any combination of any number of non-volatile memories (e.g.,flash memory) and volatile memories (e.g., DRAM, SRAM), or any othernon-transitory storage medium, or a combination thereof media. Memory502 may store an operating system (OS) 520 and an applicationenvironment 510 where one or more applications reside includingapplication 512 to be executed by processor 505.

In some embodiments, application 512 may be an application thatcaptures, stores, and/or transmits images of pallets for visualidentification in a cloud environment. Application 512 may include apallet detection engine 514, an image capture engine 515, and an imagecompression engine 516. In some embodiments, one or more of thesecomponents can be provided by another application or component that isnot part of application 512.

The pallet detection engine 514 may be configured to, in conjunctionwith the processor 505 and the communication subsystem 509, receive aping (i.e., a brief signal) from a pallet in proximity to the accessdevice 410. In some embodiments, the pallet may be configured to send aping to the communication subsystem 509 when within a certain distanceof the access device 410 (e.g., 10 feet). In some embodiments, thepallet may be configured to send a ping to the communication subsystem509 when within any communication range of the access device 410 (e.g.,50 feet), and the pallet detection engine 514 may monitor the distancebetween the access device 410 and the pallet based on the pings. In someembodiments, when the pallet is detected by the pallet detection engine514, the pallet detection engine 514 may transmit an image capturesignal to the image capture engine 515. In some embodiments, when thepallet is detected by the pallet detection engine 514 to be at aparticular distance from the access device 410 and/or in a particularorientation with respect to the access device 410 (which may be inferredfrom data collected by sensors on the pallet, such as accelerometers,gyroscopes, etc.), the pallet detection engine 514 may transmit an imagecapture signal to the image capture engine 515.

The image capture engine 515 may be configured to, in conjunction withthe processor 505, receive an image capture signal from the palletdetection engine 514 based on detection of the pallet. In response toreceiving the image capture signal, the image capture engine 515 maycapture an image of the pallet. For example, a pallet may be positionedat the beginning of a conveyor belt, with the access device 410positioned halfway down the conveyor belt and positioned six feet abovewith the camera 508 pointing down toward the conveyor belt. The palletmay include a Bluetooth LE tag programmed to send a ping (either on itsown initiative or in response to a ping from the access device 410) whenit is within six feet of the access device 410. Thus, when the pallet isdirectly below the access device 410, the pallet may transmit a ping tothe access device 410 (e.g., via the pallet detection engine 514). Thepallet detection engine 514 may transmit an image capture signal to theimage capture engine 515. The image capture engine 515 may then causethe camera 508 to capture an image of the pallet directly below theaccess device 410 as the pallet moves on the conveyor belt. In someembodiments, the image capture engine 515 may be configured to captureimages of the pallet immediately before and immediately after any repairto reduce the negative effects of changes to the pallet visualappearance.

Although described as an automated process using the pallet detectionengine 514 and the image capture engine 515, it is contemplated that insome embodiments, the pallet detection engine 514 may be omitted. Inthese embodiments, the image capture engine 515 may include softwarethat allows a user to manually initiate image captures using the camera508. For example, a user may approach a pallet with the access device410, and select an option on the user interface 506 that activates thatimage capture engine 515 and captures an image of the pallet using thecamera 508.

In some embodiments, the application 512 may further include an imagecompression engine 516. The image compression engine 516 may beconfigured to, in conjunction with the processor 505, compress imagescaptured by the camera 508 to a lower data size and/or resolution. Insome embodiments, the images captured by the camera 508 may be very highresolution. However, such a high resolution may not be needed in orderto analyze the visual features of the pallets captured in the images.Thus, the image compression engine 516 may compress the images to alower resolution that is still suitable for analysis (i.e., to thesmallest resolution in which the visual features of the pallets maystill be identified). Such compression may also reduce transmission timeof the images off of the access device 410. The compression may belossless compression, in one embodiment. Possible compression modesinclude JPLL (JPEG lossless), JLSL (JPEG-LS Lossless), J2KR (JPEG 2000Lossless), and JPLY (JPEG Lossy). In some embodiments, the imagecompression engine 516 may reduce the data size of the image file byidentifying vectors present in the image as described further herein,then transmitting the vectors or representations of the vectors foranalysis.

FIG. 6 is a block diagram illustrating a server computer 420, inaccordance with some embodiments. Server computer 420 may include aprocessor 601 coupled to a network interface 602 and a computer readablemedium 606. Server computer 420 may also include or otherwise haveaccess to a database 603 that may be internal or external to the servercomputer 420.

Processor 601 may include one or more microprocessors to execute programcomponents for performing the pallet identification functions of theserver computer 420. Network interface 602 may be configured to connectto one or more communication networks to allow the server computer 420to communicate with other entities, such as the access device, thecontroller computer, etc. Computer readable medium 606 may include anycombination of one or more volatile and/or non-volatile memories, forexample, RAM, DRAM, SRAM, ROM, flash, or any other suitable memorycomponents. Computer readable medium 606 may store code executable bythe processor 601 for implementing some or all of the image analysisfunctions of server computer 420. For example, computer readable medium606 may include code implementing a scaling and rotation engine 608, afeature identification engine 609, a spatial orientation identificationengine 610, a vector generation engine 611, a vector comparison engine612, and a data generation engine 613. In some embodiments, the scalingand rotation engine 608, the feature identification engine 609, thespatial orientation identification engine 610, and/or the vectorgeneration engine 611 may be omitted from the server computer 420, andinstead be implemented by the access device 410.

The scaling and rotation engine 608 may be configured to, in conjunctionwith the processor 601, receive an image of a pallet from an accessdevice in an image file. The scaling and rotation engine 608 may beconfigured to scale, rotate, crop and/or align the image of the palletto meet particular criteria or standards. For example, the scaling androtation engine 608 may resize the image of the pallet to be aparticular standard size, such as 1000 pixels by 1000 pixels. In anotherexample, the scaling and rotation engine 608 may be configured to cropthe image of the pallet such that only the pallet is shown (i.e.,eliminating background images). In another example, the scaling androtation engine 608 may be configured to align the image of the palletsuch that its edges are viewed as being horizontally and verticallyoriented. In another example, the scaling and rotation engine 608 may beconfigured to rotate the image of the pallet clockwise and/orcounterclockwise to change which side of the pallet is seen as being the“top” and “bottom”, i.e., a 90, 180 or 270 degree rotation. The imagemay be rotated into a standard orientation used for analysis, e.g., witha logo, arrow or other marking being right side up. In some embodiments,it may not be necessary to scale, rotate, crop and/or align the imagefor analysis. In such embodiments, it is contemplated that the scalingand rotation engine 608 may be omitted.

The feature identification engine 609 may be configured to, inconjunction with the processor 601 and the network interface 602,receive the image of the pallet. The feature identification engine 609may be configured to analyze the image to identify visual features ofthe pallet. The visual features may include any unique characteristicsor combination of characteristics that are together unique to aparticular pallet. Such visual features may include size, color,dimensions, holes, dents, text, graphics, scratches, textures, levels,depressions, nail location pattern, paint, board orientation, damage,combinations thereof, and/or the like. With respect to a pallet eitherpartially or fully formed of wood, the visual features may include woodgrain marks and patterns, such as a direction of the wood cells (e.g.,straight grain, spiral grain, interlocked, etc.), surface appearance,growth ring placement, plane of the cut (quarter sawn, flat sawn, endgrain, etc.), rate of growth, relative cell size, etc. It iscontemplated that any number of visual features may be identified. Ingeneral, a higher probability of finding a match to the pallet withgreater accuracy may result if more visual features are identified. Thefeature identification engine 608 may be configured to indicate one ormore of the visual features in the image and/or the image file. Forexample, the feature identification engine 609 may be configured toindicate the visual features in the image (e.g., by outlining each ofthe identified visual features, by adding arrows pointing to each of thevisual features, etc.). In another example, the feature identificationengine 609 may be configured to indicate the visual features in a fileseparate from or combined with the image file (e.g., by listing pixelcoordinates and/or areas in which the identified visual features arelocated). It is contemplated that the feature identification engine 609may be implemented using computer vision analysis and/or deep neuralnetworks.

The spatial orientation identification engine 610 may be configured to,in conjunction with the processor 601, receive the image and theidentified visual features from the feature identification engine 609.The spatial orientation identification engine 610 may be configured toanalyze the visual features of the image to identify the spatialorientations of the visual features. The spatial orientations maydescribe the distance between visual features and/or between a visualfeature and a fixed point, and/or the orientation of visual featureswith respect to each other and/or with respect to a fixed point. Thespatial orientation identification engine 610 may be configured toindicate the spatial orientations in a file separate from or combinedwith the image file. For example, the spatial orientation identificationengine 610 may indicate that a given wood grain marking is oriented at a45 degree angle with respect to the top of the pallet shown in theimage. It is contemplated that the spatial orientation identificationengine 610 may be implemented using computer vision analysis and/or deepneural networks.

The vector generation engine 611 may be configured to, in conjunctionwith the processor 601, receive the image, identified visual features,and spatial orientations from the spatial orientation identificationengine 610 and/or the feature identification engine 609. The vectorgeneration engine 611 may be configured to generate vectors using thevisual features and the spatial orientations. The vectors may includeordered groups of numerical values representing the visual features andthe spatial orientations. In some embodiments, the vectors may bestrings of 256 numbers.

The vector comparison engine 612 may be configured to, in conjunctionwith the processor 601, receive the vectors corresponding to the imageof the pallet from the vector generation engine 611. The vectorcomparison engine 612 may be configured to access the database 603 toretrieve sets of known vectors of visual features and spatialorientations corresponding to known pallets. In some embodiments, thevector comparison engine 612 may be configured to retrieve only sets ofknown vectors corresponding to known pallets that meet certain criteriacommon with the pallet being analyzed (e.g., being used or active in thesupply chain, in a certain region, at a certain facility, etc.). Thismay reduce the number of known vectors to which the pallet beinganalyzed needs to be compared, which may reduce processing time.

The vector comparison engine 612 may be configured to compare thereceived vectors to the known vectors to identify a matching set ofknown vectors and a corresponding matching pallet. In some embodiments,the vector comparison engine 612 may be configured to identify multiplepotential matching pallets and provide a matching score, e.g., 95% ofvisual features are matching. The multiple potential matching palletsmay be ranked from the highest matching score to the lowest matchingscore in some embodiments. The multiple potential matching pallets mayfurther be ranked based on certain criteria common with the pallet beinganalyzed (e.g., if there are two 95% matches, the match with a cycletime closer to the cycle time of the pallet being analyzed may be rankedfirst). This ranking may include data from the supply chain expected tobe associated with a pallet, such as where a matched pallet is expectedto be located.

In some embodiments, a threshold matching score may be established forwhich a match may be identified. For example, the vector comparisonengine 612 may only identify a match or matches having a matching scoregreater than or equal to 80%. If the matching score is below thethreshold (e.g., under 80%), the vector comparison engine 612 maycharacterize the pallet being analyzed as a pallet that does not alreadyexist in the database 603 (e.g., a new pallet or preexisting pallet thathas not previously been analyzed and/or entered into the database 603,or a pallet that has changed visually). Thus, the vector comparisonengine 612 may create a new entry in the database 603 for the palletbeing analyzed. The entry may include a pallet identifier (e.g., aunique identification code, name or number corresponding to the palletbeing analyzed) and the set of vectors generated by the vectorgeneration engine 611. Thus, the next time the pallet is seen in thesupply chain, it may be visually identified using the methods describedherein.

The data generation engine 613 may be configured to, in conjunction withthe processor 601, generate data associated with the pallet once thepallet has been identified and matched. The data may include, forexample, location data (i.e., where the pallet was when its image wascaptured, e.g., at a particular shipper, carrier, manufacturer, and/orfacility), whether the pallet is currently in the supply chain, a cycletime of the pallet to move through the supply chain, changes to thevisual features on the pallet, new visual features on the pallet, damageto the pallet, combinations thereof, and/or the like. The datageneration engine 613 may be configured to store the data as an entry inthe database 603 corresponding to the matched pallet. The datageneration engine 613 may be in communication with or may include one ormore sensors, such as an accelerometer, a gyroscope, a barometer, acompass, a magnetometer, and/or the like.

The data generation engine 613 may additionally or alternatively beconfigured to, in conjunction with the processor 601, perform analysisbased on identification of the pallet. For example, the data generationengine 613 may perform a detailed statistical analysis of cycle time atthe individual pallet level, including information such as region,facility, customer, date, time, pallet type, pallet manufacturer, and/orother pallet characteristics. In another example, the data generationengine 613 may perform a detailed statistical analysis of pallet damagerate by region, facility, customer, date, time, damage type, pallettype, pallet manufacturer, and/or other pallet characteristics. In stillanother example, the data generation engine 613 may perform a detailedstatistical analysis of known and unknown pallet paths through thepallet network of manufacturer, distributors, retailers, collectors,and/or service centers. In another example, the data generation engine613 may monitor service center repair quality and efficiency. In stillanother example, the data generation engine 613 may make a periodicevaluation of identification accuracy to guide identification methodrefinement.

Methods for Pallet Identification

A variety of methods may be implemented by the above-described systems.FIG. 7 is a flow chart illustrating an exemplary method for palletidentification, in accordance with some embodiments. At process block710, an image file 705 is received at a server computer located in acloud. The image file 705 may depict a plurality of visual features 706organized in a plurality of spatial orientations 707 on a pallet. Insome embodiments, the pallet may not include a physical tag showing orstoring a pallet identifier. In other words, the pallet may not have adirect visual or electronic means of providing its identity. In someembodiments, the pallet is wooden. The image file 705 may have beengenerated by an imaging device (e.g., a camera) located at a facilityhousing the pallet in a supply chain. In some embodiments, the imagingdevice may be or may be incorporated in a mobile device (e.g., asmartphone). The pallet may be included in a plurality of known palletsin the supply chain. In some embodiments, the image file 705 may berotated, cropped, aligned and/or scaled. Further at process block 710, aset of unidentified vectors associated with the pallet may be generatedusing the plurality of visual features and the plurality of spatialorientations.

At process block 715, a database may be accessed. The database may storea plurality of sets of known vectors in association with a plurality ofknown pallet identifiers corresponding to the plurality of known palletsin the supply chain. Sets of vectors may have been generated for palletsin the supply chain based on the visual features and/or spatialorientations of those pallets, as described further herein. The palletidentifiers may include any combination of letters, numbers, and/orsymbols that may be used to uniquely identify each pallet. In otherwords, each unique pallet may correspond to a unique pallet identifier.

At process block 720, the set of unidentified vectors may be compared tothe plurality of sets of known vectors to identify a matching set ofknown vectors and an associated known pallet identifier. In someembodiments, comparing the set of unidentified vectors to the pluralityof sets of known vectors may include identifying at least one differencebetween the set of unidentified vectors and the matching set of knownvectors. The at least one difference may be indicative of changes to thepallet, e.g., new damage to the pallet, new markings on the pallet, etc.In some embodiments, the set of unidentified vectors may be compared toa subset of the plurality of sets of known vectors stored in thedatabase (i.e., less than all of the sets of known vectors stored in thedatabase). For example, the set of unidentified vectors may only becompared to sets of known vectors associated with pallets that aresupposed to be in the same region as the pallet having the set ofunidentified vectors. By narrowing down the number of sets of knownvectors that the set of unidentified vectors are compared to, processingtime may be reduced.

At process block 725, data associated with the pallet may be generated.In some embodiments, the data associated with the pallet may include acycle time of the pallet to move through the supply chain. In someembodiments, the data associated with the pallet may include the atleast one difference between the set of unidentified vectors and thematching set of known vectors (e.g., visual damage to the pallet). Atprocess block 730, the data may be stored as an entry in the databasecorresponding to the associated known pallet identifier. In other words,data corresponding to the known pallet may be updated and/or added basedon its identification in the supply chain.

Various advantages may be observed by implementing disclosed embodimentsof the invention. For example, embodiments of the invention may beimplemented with low cost hardware resources to capture images and lowcost or free software resources to process and identify pallet images.In another example, embodiments of the invention may be efficient inthat they do not require modification of existing pallet manufacturingprocesses or physical manipulation of the pallet structure. In anotherexample, embodiments of the invention may be robust in that they canidentify damaged pallets in situations that could cause a physical labelto be lost. In still another example, embodiments of the invention mayuse mobile phone camera to enable pallet identification in any setting.

As noted, the computer-readable medium may include transient media, suchas a wireless broadcast or wired network transmission, or storage media(that is, non-transitory storage media), such as a hard disk, flashdrive, compact disc, digital video disc, Blu-ray disc, or othercomputer-readable media. The computer-readable medium may be understoodto include one or more computer-readable media of various forms, invarious examples.

In the foregoing description, aspects of the application are describedwith reference to specific embodiments thereof, but those skilled in theart will recognize that the invention is not limited thereto. Thus,while illustrative embodiments of the application have been described indetail herein, it is to be understood that the inventive concepts may beotherwise variously embodied and employed, and that the appended claimsare intended to be construed to include such variations, except aslimited by the prior art. Various features and aspects of theabove-described invention may be used individually or jointly. Further,embodiments can be utilized in any number of environments andapplications beyond those described herein without departing from thebroader spirit and scope of the specification. The specification anddrawings are, accordingly, to be regarded as illustrative rather thanrestrictive. For the purposes of illustration, methods were described ina particular order. It should be appreciated that in alternateembodiments, the methods may be performed in a different order than thatdescribed.

Where components are described as performing or being “configured to”perform certain operations, such configuration can be accomplished, forexample, by designing electronic circuits or other hardware to performthe operation, by programming programmable electronic circuits (e.g.,microprocessors, or other suitable electronic circuits) to perform theoperation, or any combination thereof.

The various illustrative logical blocks, modules, circuits, andalgorithm steps described in connection with the embodiments disclosedherein may be implemented as electronic hardware, computer software,firmware, or combinations thereof. To clearly illustrate thisinterchangeability of hardware and software, various illustrativecomponents, blocks, modules, circuits, and steps have been describedabove generally in terms of their functionality. Whether suchfunctionality is implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem. Skilled artisans may implement the described functionality invarying ways for each particular application, but such implementationdecisions should not be interpreted as causing a departure from thescope of the present invention.

The techniques described herein may also be implemented in electronichardware, computer software, firmware, or any combination thereof. Suchtechniques may be implemented in any of a variety of devices such asgeneral purposes computers, wireless communication device handsets, orintegrated circuit devices having multiple uses including application inwireless communication device handsets and other devices. Any featuresdescribed as modules or components may be implemented together in anintegrated logic device or separately as discrete but interoperablelogic devices. If implemented in software, the techniques may berealized at least in part by a computer-readable data storage mediumcomprising program code including instructions that, when executed,performs one or more of the methods described above. Thecomputer-readable data storage medium may form part of a computerprogram product, which may include packaging materials. Thecomputer-readable medium may comprise memory or data storage media, suchas random access memory (RAM) such as synchronous dynamic random accessmemory (SDRAM), read-only memory (ROM), non-volatile random accessmemory (NVRAM), electrically erasable programmable read-only memory(EEPROM), FLASH memory, magnetic or optical data storage media, and thelike. The techniques additionally, or alternatively, may be realized atleast in part by a computer-readable communication medium that carriesor communicates program code in the form of instructions or datastructures and that can be accessed, read, and/or executed by acomputer, such as propagated signals or waves.

The program code may be executed by a processor, which may include oneor more processors, such as one or more digital signal processors(DSPs), general purpose microprocessors, an application specificintegrated circuits (ASICs), field programmable logic arrays (FPGAs), orother equivalent integrated or discrete logic circuitry. Such aprocessor may be configured to perform any of the techniques describedin this disclosure. A general purpose processor may be a microprocessor;but in the alternative, the processor may be any conventional processor,controller, microcontroller, or state machine. A processor may also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration. Accordingly, the term “processor,” as used herein mayrefer to any of the foregoing structure, any combination of theforegoing structure, or any other structure or apparatus suitable forimplementation of the techniques described herein. In addition, in someaspects, the functionality described herein may be provided withindedicated software modules or hardware modules configured for encodingand decoding, or incorporated in a combined encoder-decoder (CODEC).

What is claimed is:
 1. A computer-implemented method of identifying apallet, the method comprising: receiving, at a computing device, animage captured by an imaging device, wherein the image depicts a visualfeature and a corresponding spatial orientation associated with apallet; accessing a database storing one or more known visual featureswith corresponding spatial orientations, each corresponding to a uniqueone of one or more known pallets associated with a supply chain;matching the visual feature and the corresponding spatial orientationassociated with the pallet with a known visual feature and correspondingspatial orientation in the one or more known visual features withcorresponding spatial orientations in the database to uniquely identifythe pallet as a known pallet from the one or more known palletsassociated with the supply chain; and storing data in the database forthe known pallet.
 2. The computer-implemented method of claim 1, whereinthe pallet does not include a physical tag showing or storing a palletidentifier.
 3. The computer-implemented method of claim 1, wherein thedata comprises: location data indicating a location where the pallet iswhen the image is captured; changes to the visual feature on the palletor new visual features on the pallet; a cycle time of the pallet to movethrough the supply chain; a statistical analysis of a pallet damagerate; or a statistical analysis of quality of repairs made to damage onthe pallet.
 4. The computer-implemented method of claim 1, furthercomprising generating a separate file from the image, wearing theseparate file comprises: pixel coordinates of the visual feature in theimage; and an angle orientation of the visual feature in the image. 5.The computer-implemented method of claim 1, wherein matching the visualfeature and the corresponding spatial orientation associated with thepallet with the known visual feature and corresponding spatialorientation comprises: identifying a difference between the visualfeature and the corresponding spatial orientation and the known visualfeature and corresponding spatial orientation, wherein the data includesthe difference.
 6. The computer-implemented method of claim 5, whereinthe difference is indicative of damage to the pallet.
 7. Thecomputer-implemented method of claim 1, wherein the pallet is located ata facility associated with a region, and wherein matching the visualfeature and the corresponding spatial orientation associated with thepallet with the known visual feature and corresponding spatialorientation is based at least in part on matching the region.
 8. Anon-transitory computer-readable medium comprising instructions that,when executed by one or more processors, cause the one or moreprocessors to perform operations comprising: receiving, at a computingdevice, an image captured by an imaging device, wherein the imagedepicts a visual feature and a corresponding spatial orientationassociated with a pallet; accessing a database storing one or more knownvisual features with corresponding spatial orientations, eachcorresponding to a unique one of one or more known pallets associatedwith a supply chain; matching the visual feature and the correspondingspatial orientation associated with the pallet with a known visualfeature and corresponding spatial orientation in the one or more knownvisual features with corresponding spatial orientations in the databaseto uniquely identify the pallet as a known pallet from the one or moreknown pallets associated with the supply chain; and storing data in thedatabase for the known pallet.
 9. The non-transitory computer-readablemedium of claim 8, wherein the imaging device comprises a mobilehandheld computing device.
 10. The non-transitory computer-readablemedium of claim 8, wherein the operations further comprise rotating theimage such that edges of the pallet are oriented in the imagehorizontally or vertically.
 11. The non-transitory computer-readablemedium of claim 8, wherein the operations further comprise, scaling theimage such that a portion of the image depicting the pallet is apredetermined standard size.
 12. The non-transitory computer-readablemedium of claim 8, wherein the visual feature comprises a feature on asurface of the pallet.
 13. The non-transitory computer-readable mediumof claim 8, wherein the visual feature comprises wood grain marks orpatterns on the surface of the pallet.
 14. The non-transitorycomputer-readable medium of claim 8, wherein the visual featurecomprises one or more selections from a group consisting of: holes,dents, textures, depressions, nail locations, and surface damage on thesurface of the pallet.
 15. A device comprising: one or more processors;and one or more memory devices comprising instructions that, whenexecuted by the one or more processors, cause the one or more processorsto perform operations comprising: receiving, at a computing device, animage captured by an imaging device, wherein the image depicts a visualfeature and a corresponding spatial orientation associated with apallet; accessing a database storing one or more known visual featureswith corresponding spatial orientations, each corresponding to a uniqueone of one or more known pallets associated with a supply chain;matching the visual feature and the corresponding spatial orientationassociated with the pallet with a known visual feature and correspondingspatial orientation in the one or more known visual features withcorresponding spatial orientations in the database to uniquely identifythe pallet as a known pallet from the one or more known palletsassociated with the supply chain; and storing data in the database forthe known pallet.
 16. The device of claim 15, wherein the visual featurecomprises dimensions of the pallet.
 17. The device of claim 15, whereinthe spatial orientation comprises a location of the visual feature onthe pallet.
 18. The device of claim 15, wherein the operations furthercomprise encoding the visual feature and the corresponding spatialorientation as a numerical vector.
 19. The device of claim 15, whereinthe spatial orientation comprises a distance between the visual featureand another visual feature or a fixed point on the pallet.
 20. Thedevice of claim 15, wherein the operations further comprise: accessing acycle time in the supply chain for the pallet; accessing a plurality ofknown cycle times corresponding to one or more known pallets; andmatching the cycle time with a known cycle time in the plurality ofknown cycle times.